Evidence map›Paper›PMID 35314645›Full record

ReviewTomography (Ann Arbor, Mich.)2022

Stereogram of the Living Heart, Lung, and Adjacent Structures.

Yu Izawa, Tatsuya Nishii, Shumpei Mori

Abstract readReview
In one paragraph

Review in Tomography (Ann Arbor, Mich.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yu IzawaDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Hyogo 650-0017, Japan.ORCID 0000-0002-2688-3468
Tatsuya NishiiDepartment of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka 564-8565, Japan.
Shumpei MoriUCLA Cardiac Arrhythmia Center, UCLA Health System, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Innovations in invasive cardiovascular diagnostics and therapeutics, not only limited to transcatheter approaches but also involving surgical approaches, are based on a precise appreciation of the three-dimensional living heart anatomy. Rapid advancements in three-dimensional cardiovascular imaging technologies in the 21st century have supported such innovations through the periprocedural assessment of the clinical anatomy of the living heart. However, even if high-resolution volume-rendered images are reconstructed, they cannot provide appropriate depth perception when displayed and shared on a two-dimensional display, which is widely used in clinical settings. Currently, images reconstructed from clinical datasets can visualize fine details of the cardiovascular anatomy. Therefore, this is an optimal time for cardiologists and cardiac surgeons to revisit the classic technology, stereopsis, and obtain bonus information from carefully reconstructed clinical images. Using anaglyphs or cross/uncross-fusion of paired images, striking depth perception can be readily obtained without the need for expensive equipment. This conventional technique, when applied to high-resolution volume-rendered images, may help in obtaining appropriate diagnostics, choosing optimal therapeutics, securing procedural success, and preventing complications. Furthermore, it can be used for anatomical education. In this review, we demonstrate multiple stereoscopic images reconstructed from cardiac computed tomographic datasets and discuss their clinical and educational implications.

Indexed as

HeartThoraxImaging, Three-DimensionalLunganaglyphanatomycomputed tomographyheartstereogram

Identifiers

PMID35314645
PMCPMC8938811

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.